Once upon a time, the black box in Machine Learning models was a mysterious thing. Data scientists would say “Oh, it’s a black box, we can’t understand it” and “We don’t know why it made that decision”

While it did what it was supposed to, we didn’t know how it arrived at that decision.

I have good news! The black box is no longer mysterious

Gone are the days when the black box was incomprehensible, impenetrable by our understanding. What was seemingly impossible is now possible. We can actually understand black boxes very, very easily and understand the decisions it creates and then the decisions it makes.

White box: Equations out of black box

What’s amazing is that we can actually create white boxes or equations out of the black boxes and plug in the numbers and solve the equations and understand why it arrives at the decision it does.

What’s interesting is that the white boxes are very useful and extremely accurate in understanding the black box itself.

Many industries can benefit

This knowledge is quite useful for medicine, pharmaceuticals, getting your mortgage or loan approved from banks, getting your insurance approved from car insurance or other companies. And also, it’s very important for self-driving cars.

In a nutshell, this is great news for the artificial intelligence world.

Where ever AI is heavily utilized, there will be a transformation in the understanding of how AI actually forms a decision and how it comes up with an equation within that black box.

Tada, now you can actually unravel that black box and understand really what’s going on behind the black box.

More industries can adapt to Artificial Intelligence

As a data consultant, I see this as a great step forward in research, making it easier for AI to be adopted across more industries.

This understanding of how black box comes to a decision that it does, can actually help quantify the risk of black box by answering where and why it’s likely to get something wrong. So, you can actually go back and improve on the data and the training and architecture itself, and the process of creating a white box gets much simple.

First, you actually have to create the black box itself, so you do your normal model training. Once the training is done, you create a white box model on top of the black box.

Mind blowing, isn’t it?

It’s a mind-blowing new piece of research within AI, and I definitely want to start helping my clients with this tool.

So, if you have a black box that you would like help with, get in contact with me. I can definitely help you with that. And if you are looking to unravel or create white boxes out of your black boxes; book your free session now!